SoroushVahidi/scidocs huggingface dataset:
Combining Confocal Imaging and Descattering
(2008)

In translucent objects, light paths are affected by multiple scattering, which is polluting any observation. Confocal imaging reduces the influence of such global illumination effects by carefully focusing illumination and viewing rays from a large aperture to a specific location within the object volume. The selected light paths still contain some global scattering contributions, though. Descattering based on high frequency illumination serves the same purpose. It removes the global component from observed light paths. We demonstrate that confocal imaging and descattering are orthogonal and propose a novel descattering protocol that analyzes the light transport in a neighborhood of light transport paths. In combination with confocal imaging, our descattering method achieves optical sectioning in translucent media with higher contrast and better resolution.
A Survey on Survey of Migration of Legacy Systems
(2016)

Legacy systems are mission critical complex systems which are hard to maintain owing to shortage of skill sets and monolithic code architecture with tightly coupled tiers, all of which are indication of obsoleteness of the system technology. Thus, they have to be migrated to the latest technology(ies). Migration is an offspring research in Software Engineering which is almost three decades old research and numerous publications have emerged in many topics in the migration domain with focus areas of code migration, architecture migration, case study on migration and effort estimation on migration. In addition, various survey works surveying different aspects of migration have also emerged. This paper provides a survey of these survey works in order to provide a consolidation of these survey works. As an outcome of the survey on survey of migration, a road map of migration evolution from the early stages to the recent works on migration comprising of significant milestones in migration research has been presented in this work.
Distance Preserving Dimension Reduction for Manifold Learning
(2007)

Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data analysis and bioinformatics. The focus of this paper is on developing algorithms for reducing the computational complexity of manifold learning algorithms, in particular, we consider the case when the number of features is much larger than the number of data points. To handle the large number of features, we propose a preprocessing method, distance preserving dimension reduction (DPDR). It produces t-dimensional representations of the high-dimensional data, wheret is the rank of the original dataset. It exactly preserves the Euclidean L2-norm distances as well as cosine similarity measures between data points in the original space. With the original data projected to the t-dimensional space, manifold learning algorithms can be executed to obtain lower dimensional parameterizations with substantial reduction in computational cost. Our experimental results illustrate that DPDR significantly reduces computing time of manifold learning algorithms and produces low-dimensional parameterizations as accurate as those obtained from the original datasets.
Quantum Field Theory in Curved Spacetime
(1994)

We review the mathematically rigorous formulation of the quantum theory of a linear field propagating in a globally hyperbolic spacetime. This formulation is accomplished via the algebraic approach, which, in essence, simultaneously admits all states in all possible (unitarily inequivalent) Hilbert space constructions. The physically nonsingular states are restricted by the requirement that their two-point function satisfy the Hadamard condition, which insures that the ultra-violet behavior of the state be similar to that of the vacuum state in Minkowski spacetime, and that the expected stress-energy tensor in the state be finite. We briefly review the Unruh and Hawking effects from the perspective of the theoretical framework adopted here. A brief discussion also is given of several open issues and questions in quantum field theory in curved spacetime regarding the treatment of “backreaction”, the validity of some version of the “averaged null energy condition”, and the formulation and properties of quantum field theory in causality violating
Tensor2Tensor for Neural Machine Translation
(2018)

Tensor2Tensor is a library for deep learning models that is very well-suited for neural machine translation and includes the reference implementation of the state-of-the-art Transformer model. 1 Neural Machine Translation Background Machine translation using deep neural networks achieved great success with sequence-tosequence models Sutskever et al. (2014); Bahdanau et al. (2014); Cho et al. (2014) that used recurrent neural networks (RNNs) with LSTM cells Hochreiter and Schmidhuber (1997). The basic sequence-to-sequence architecture is composed of an RNN encoder which reads the source sentence one token at a time and transforms it into a fixed-sized state vector. This is followed by an RNN decoder, which generates the target sentence, one token at a time, from the state vector. While a pure sequence-to-sequence recurrent neural network can already obtain good translation results Sutskever et al. (2014); Cho et al. (2014), it suffers from the fact that the whole input sentence needs to be encoded into a single fixed-size vector. This clearly manifests itself in the degradation of translation quality on longer sentences and was partially overcome in Bahdanau et al. (2014) by using a neural model of attention. Convolutional architectures have been used to obtain good results in word-level neural machine translation starting from Kalchbrenner and Blunsom (2013) and later in Meng et al. (2015). These early models used a standard RNN on top of the convolution to generate the output, which creates a bottleneck and hurts performance. Fully convolutional neural machine translation without this bottleneck was first achieved in Kaiser and Bengio (2016) and Kalchbrenner et al. (2016). The model in Kaiser and Bengio (2016) (Extended Neural GPU) used a recurrent stack of gated convolutional layers, while the model in Kalchbrenner et al. (2016) (ByteNet) did away with recursion and used left-padded convolutions in the decoder. This idea, introduced in WaveNet van den Oord et al. (2016), significantly improves efficiency of the model. The same technique was improved in a number of neural translation models recently, including Gehring et al. (2017) and Kaiser et al. (2017).
Semantics in Visual Information Retrieval
(1999)

V isual information retrieval systems have entered a new era. First-generation systems allowed access to images and videos through textual data. 1,2 Typical searches for these systems include, for example, " all images of paintings of the Florentine school of the 15th century " or " all images by Cezanne with landscapes. " Such systems expressed information through alphanumeric keywords or scripts. They employed representation schemes like relational models, frame models, and object-oriented models. On the other hand, current-generation retrieval systems support full retrieval by visual content. 3,4 Access to visual information is not only performed at a conceptual level, using keywords as in the textu-al domain, but also at a perceptual level, using objective measurements of visual content. In these systems, image processing, pattern recognition , and computer vision constitute an integral part of the system's architecture and operation. They objectively analyze pixel distribution and extract the content descriptors automatically from raw sensory data. Image content descriptors are commonly represented as feature vectors, whose elements correspond to significant parameters that model image attributes. Therefore, visual attributes are regarded as points in a multidimen-sional feature space, where point closeness reflects feature similarity. These advances (for comprehensive reviews of the field, see the " Further Reading " sidebar) have paved the way for third-generation systems, featuring full multimedia data management and networking support. Forthcoming standards such as MPEG-4 and MPEG-7 (see the Nack and Lindsay article in this issue) provide the framework for efficient representation, processing, and retrieval of visual information. Yet many problems must still be addressed and solved before these technologies can emerge. An important issue is the design of indexing structures for efficient retrieval from large, possibly distributed , multimedia data repositories. To achieve this goal, image and video content descriptors can be internally organized and accessed through multidimensional index structures. 5 A second key problem is to bridge the semantic gap between the system and users. That is, devise representations capturing visual content at high semantic levels especially relevant for retrieval tasks. Specifically, automatically obtaining a representation of high-level visual content remains an open issue. Virtually all the systems based on automatic storage and retrieval of visual information proposed so far use low-level perceptual representations of pictorial data, which have limited semantics. Building up a representation proves tantamount to defining a model of the world, possibly through a formal description language, whose semantics capture only a few …
A Dynamic Method to Forecast the Wheel Slip for Antilock Braking System and Its Experimental Evaluation
(2009)

The control of an antilock braking system (ABS) is a difficult problem due to its strongly nonlinear and uncertain characteristics. To overcome this difficulty, the integration of gray-system theory and sliding-mode control is proposed in this paper. This way, the prediction capabilities of the former and the robustness of the latter are combined to regulate optimal wheel slip depending on the vehicle forward velocity. The design approach described is novel, considering that a point, rather than a line, is used as the sliding control surface. The control algorithm is derived and subsequently tested on a quarter vehicle model. Encouraged by the simulation results indicating the ability to overcome the stated difficulties with fast convergence, experimental results are carried out on a laboratory setup. The results presented indicate the potential of the approach in handling difficult real-time control problems.
A survey of RDF data management systems
(2016)

RDF is increasingly being used to encode data for the semantic web and data exchange. There have been a large number of works that address RDF data management following different approaches. In this paper we provide an overview of these works. This review considers centralized solutions (what are referred to as warehousing approaches), distributed solutions, and the techniques that have been developed for querying linked data. In each category, further classifications are provided that would assist readers in understanding the identifying characteristics of different approaches.
Efficient Parallel Graph Exploration on Multi-Core CPU and GPU
(2011)

Graphs are a fundamental data representation that has been used extensively in various domains. In graph-based applications, a systematic exploration of the graph such as a breadth-first search (BFS) often serves as a key component in the processing of their massive data sets. In this paper, we present a new method for implementing the parallel BFS algorithm on multi-core CPUs which exploits a fundamental property of randomly shaped real-world graph instances. By utilizing memory bandwidth more efficiently, our method shows improved performance over the current state-of-the-art implementation and increases its advantage as the size of the graph increases. We then propose a hybrid method which, for each level of the BFS algorithm, dynamically chooses the best implementation from: a sequential execution, two different methods of multicore execution, and a GPU execution. Such a hybrid approach provides the best performance for each graph size while avoiding poor worst-case performance on high-diameter graphs. Finally, we study the effects of the underlying architecture on BFS performance by comparing multiple CPU and GPU systems, a high-end GPU system performed as well as a quad-socket high-end CPU system.
Optimising Results from Minimal Access Cranial Suspension Lifting (MACS-Lift)
(2005)

Between November 1999 and February 2005, 450 minimal access cranial suspension (MACS) lifts were performed. Starting with the idea of suspension for sagging soft tissues using permanent purse-string sutures, a new comprehensive approach to facial rejuvenation was developed in which the vertical vector appeared to be essential. The neck is corrected by extended submental liposuction and strong vertical traction on the lateral part of the platysma by means of a first vertical purse-string suture. The volume of the jowls and the cheeks is repositioned in a cranial direction with a second, slightly oblique purse-string suture. The descent of the midface is corrected by suspending the malar fat pad in a nearly vertical direction. In 23 cases (5.1%), the result in the neck was unsatisfactory, and additional work had to be done secondarily, or in later cases, primarily. The problem that appeared was unsatisfactory correction of platysmal bands (resolved with an additional anterior cervicoplasty) or vertical skin folds that appeared in the infralobular region (corrected with an additional posterior cervicoplasty). This article describes two ancillary procedures that, although not frequently necessary, can optimise the result of MACS lifting.
A Survey of Mobile Cloud Computing Applications: Perspectives and Challenges
(2015)

As mobile computing has been developed for decades, a new model for mobile computing, namely, mobile cloud computing, emerges resulting from the marriage of powerful yet affordable mobile devices and cloud computing. In this paper we survey existing mobile cloud computing applications, as well as speculate future generation mobile cloud computing applications. We provide insights for the enabling technologies and challenges that lie ahead for us to move forward from mobile computing to mobile cloud computing for building the next generation mobile cloud applications. For each of the challenges, we provide a survey of existing solutions, identify research gaps, and suggest future research areas.
Human activity recognition using inertial sensors with invariance to sensor orientation
(2012)

This work deals with the task of human daily activity recognition using miniature inertial sensors. The proposed method reduces sensitivity to the position and orientation of the sensor on the body, which is inherent in traditional methods, by transforming the observed signals to a “virtual” sensor orientation. By means of this computationally low-cost transform, the inputs to the classification algorithm are made invariant to sensor orientation, despite the signals being recorded from arbitrary sensor placements. Classification results show that improved performance, in terms of both precision and recall, is achieved with the transformed signals, relative to classification using raw sensor signals, and the algorithm performs competitively compared to the state-of-the-art. Activity recognition using data from a sensor with completely unknown orientation is shown to perform very well over a long term recording in a real-life setting.
A simple circularly polarized loop tag antenna for increased reading distance
(2014)

A simple circularly polarized (CP) loop tag antenna is proposed to overcome the polarization mismatch problem between reader antenna and tag antenna. Good CP radiation can be achieved by introducing an open gap onto the square loop. Also, the technique of loading a matching stub across the RFID chip is applied to the proposed loop tag antenna, and desirable impedance matching between the antenna and RFID chip can be realized by tuning the matching stub. The proposed loop tag antenna shows good reading distance performance, and its measured reading distance reaches to 17.6 m.
Business artifacts: An approach to operational specification
(2003)

Any business, no matter what physical goods or services it produces, relies on business records. It needs to record details of what it produces in terms of concrete information. Business artifacts are a mechanism to record this information in units that are concrete, identifiable, self-describing, and indivisible. We developed the concept of artifacts, or semantic objects, in the context of a technique for constructing formal yet intuitive operational descriptions of a business. This technique, called OpS (Operational Specification), was developed over the course of many business-transformation and business-process-integration engagements for use in IBM’s internal processes as well as for use with customers. Business artifacts (or business records) are the basis for the factorization of knowledge that enables the OpS technique. In this paper we present a comprehensive discussion of business artifacts—what they are, how they are represented, and the role they play in operational business modeling. Unlike the more familiar and popular concept of business objects, business artifacts are pure instances rather than instances of a taxonomy of types. Consequently, the key operation on business artifacts is recognition rather than classification.
Bitcoin and Beyond: A Technical Survey on Decentralized Digital Currencies
(2015)

Besides attracting a billion dollar economy, Bitcoin revolutionized the field of digital currencies and influenced many adjacent areas. This also induced significant scientific interest. In this survey, we unroll and structure the manyfold results and research directions. We start by introducing the Bitcoin protocol and its building blocks. From there we continue to explore the design space by discussing existing contributions and results. In the process, we deduce the fundamental structures and insights at the core of the Bitcoin protocol and its applications. As we show and discuss, many key ideas are likewise applicable in various other fields, so that their impact reaches far beyond Bitcoin itself.
QoS-aware middleware for Web services composition
(2004)

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online business-to-business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different quality of service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming.
To See or not to See – Innovative Display Technologies as Enablers for Ergonomic Cockpit Concepts Ergonomic requirements future mobility future functionality
(2014)

Introduction Given the fact that the driving task will remarkably change by the increase of assistance and information systems in the future innovative display technologies play a central role for the ergonomic realization of the driver vehicle interaction. Increasing assistance and even automation of the driving task do not lead to a decrease or disappearance of visual information but instead request new and in some cases revolutionary concepts to close the loop between driver, vehicle and traffic environment. Augmenting information in contact analog head-up-displays for navigation and driver assistance is a very promising approach. Replacement of mirrors via camera monitor systems is a further example. Free programmable cluster instruments in combination with HUD promise to resolve the problem of information density produced by an increasing amount of ADAS and IVIS functionality.
An electrostatic gripper for flexible objects
(2017)

We demonstrate a flexible, electrostatic adhesive gripper designed to controllably grasp and manipulate soft goods in space. The 8-fingered gripper has 50 cm2 of active electrodes operating at 3 kV. It generates electrostatic adhesion forces up to 3.5 N (0.70 kPa) on Ge-coated polyimide film and 1.2 N on MLI blanket, a film composite used for satellite thermal insulation. Extremely low-force gripper engagement (0.08 N) and release (0.04 N) of films is ideal for micro-gravity. Individual fingers generate shear adhesion forces up to 4.76 N (5.04 kPa) using electrostatic adhesive and 45.0 N (47.6 kPa) with a hybrid electrostatic / gecko adhesive. To simulate a satellite servicing task, the gripper was mounted on a 7-DoF robot arm and performed a supervised grasp, manipulate, and release sequence on a hanging, Al-coated PET film.
The optimum received power levels of uplink non-orthogonal multiple access (NOMA) signals
(2017)

Non-orthogonal multiple access (NOMA) has been recently considered as a promising multiple access technique for fifth generation (5G) mobile networks as an enabling technology to meet the demands of low latency, high reliability, massive connectivity, and high throughput. The two dominants types of NOMA are: power-domain and code-domain. The key feature of power-domain NOMA is to allow different users to share the same time, frequency, and code, but with different power levels. In code-domain NOMA, different spread-spectrum codes are assigned to different users and are then multiplexed over the same time-frequency resources. This paper concentrates on power-domain NOMA. In power-domain NOMA, Successive Interference Cancellation (SIC) is employed at the receiver. In this paper, the optimum received uplink power levels using a SIC detector is determined analytically for any number of transmitters. The optimum uplink received power levels using the SIC decoder in NOMA strongly resembles the μ-law encoding used in pulse code modulation (PCM) speech companders.